GenAI Solutions Architect - Energy & Utilities (AWS)

Amazon Web Services (AWS); Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

Amazon Web Services (AWS) is seeking an experienced Data and AI Solutions Architect to drive GenAI adoption for energy customers. You will prototype, architect, and deliver end-to-end AI systems using Bedrock, AgentCore, and related tools, bridging frontier AI with real-world energy operations.

The role requires deep analytics, customer engagement with executive stakeholders, and the ability to publish reference architectures and blueprints that accelerate GenAI deployment across regulated

Qualifications

• Bachelor's degree in computer science, engineering, mathematics or equivalent.
• Experience in IT development or consulting in software or Internet industries.
• Experience in cloud computing, systems engineering, infrastructure, security, or data & analytics.
• Experience in design, implementation, or consulting on applications and infrastructures.
• Experience communicating with executive stakeholders.

Responsibilities

• Design and deliver GenAI solutions for energy customers across domains.
• Architect end-to-end AI pipelines integrating models with energy platforms.
• Build production-grade proof-of-concepts demonstrating agentic capabilities.
• Lead technical engagements with energy engineering teams on analytics and AI architectures.
• Develop reference architectures and reusable blueprints for GenAI adoption.

Skills

IT development experience

Executive communication

Cloud computing

Data & analytics

Security & infrastructure

Education

Bachelor's degree in CS/engineering/math

Tools

Amazon Bedrock

AgentCore

Claude Code

Codex

Kiro

Job description

Amazon Web Services (AWS) is seeking an experienced Data and AI Solutions Architect to drive GenAI adoption for energy customers. You will prototype, architect, and deliver end-to-end AI systems using Bedrock, AgentCore, and related tools, bridging frontier AI with real-world energy operations.

The role requires deep analytics, customer engagement with executive stakeholders, and the ability to publish reference architectures and blueprints that accelerate GenAI deployment across regulated